Prostate cancer is the most common malignancy in men and a leading cause of cancer mortality among males in the United States. Large geographical variation and racial disparities exist in its survival rate after diagnosis. We will develop new and 0exible statistical methods of spatial survival model to estimate cancer survival. We will apply the proposed method to analyze the prostate cancer data within Louisiana from the Surveillance, Epidemiology, and End Results program and within South Carolina from the South Carolina Central Cancer Registry. We will use this analysis to investigate the spatial patterns and racial disparities of prostate cancer in Louisiana and South Carolina. We will conduct a complete simulation study to compare the performances of existing spatial survival models, and it can help the practitioners or researchers involved in cancer studies to select the right spatial survival model. The proposed method may possibly be extended to include more complex situations in the future, such as groupings and time variations, in epidemiological cancer study.